Literature DB >> 20164042

Computer aided system for segmentation and visualization of microcalcifications in digital mammograms.

Branimir Reljin1, Zorica Milosević, Tomislav Stojić, Irini Reljin.   

Abstract

Two methods for segmentation and visualization of microcalcifications in digital or digitized mammograms are described. First method is based on modern mathematical morphology, while the second one uses the multifractal approach. In the first method, by using an appropriate combination of some morphological operations, high local contrast enhancement, followed by significant suppression of background tissue, irrespective of its radiology density, is obtained. By iterative procedure, this method highly emphasizes only small bright details, possible microcalcifications. In a multifractal approach, from initial mammogram image, a corresponding multifractal "images" are created, from which a radiologist has a freedom to change the level of segmentation. An appropriate user friendly computer aided visualization (CAV) system with embedded two methods is realized. The interactive approach enables the physician to control the level and the quality of segmentation. Suggested methods were tested through mammograms from MIAS database as a gold standard, and from clinical praxis, using digitized films and digital images from full field digital mammograph.

Mesh:

Year:  2009        PMID: 20164042     DOI: 10.2478/v10042-009-0076-1

Source DB:  PubMed          Journal:  Folia Histochem Cytobiol        ISSN: 0239-8508            Impact factor:   1.698


  3 in total

1.  Mathematical morphology-based approach to the enhancement of morphological features in medical images.

Authors:  Yoshitaka Kimori
Journal:  J Clin Bioinforma       Date:  2011-12-16

2.  Breast cancer evaluation by fluorescent dot detection using combined mathematical morphology and multifractal techniques.

Authors:  Branimir Reljin; Milorad Paskas; Irini Reljin; Korski Konstanty
Journal:  Diagn Pathol       Date:  2011-03-30       Impact factor: 2.644

3.  Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement.

Authors:  Yoshitaka Kimori
Journal:  J Synchrotron Radiat       Date:  2013-09-25       Impact factor: 2.616

  3 in total

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